syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.slice module

class syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.slice.SliceSampler(log_density, scale, random_state)[source]

Bases: object

sample(init_sample, num_samples, burn, thin)[source]

Return type:: List[ndarray]

syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.slice.gen_random_direction(dimension, random_state)[source]

Return type:: ndarray

syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.slice.slice_sampler_step_out(log_pivot, scale, sliced_log_density, random_state)[source]

Return type:: Tuple[float, float]

syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.slice.slice_sampler_step_in(lower_bound, upper_bound, log_pivot, sliced_log_density, random_state)[source]

Find the right amount of movement along with a random_direction

Return type:: float